# series

## What Book should I Read Next?

The platforms I use should have plenty of data to help me solve this problem. However, Libby — through the Boston Public…

## End to End Time Series Analysis and Modelling

We are ready for exploratory data analysis!Exploratory Data Analysis (EDA)Let’s see what the closing price looks like:And you get:Closing price of…

## An Introduction on Time Series Forecasting with Simple Neural Networks & LSTM

Photo Credit: PixabayAn Introduction on Time Series Forecasting with Simple Neural Networks & LSTMHow to develop Artificial Neural Networks and LSTM recurrent…

## Time Series in Python — Exponential Smoothing and ARIMA processes

Time Series in Python — Exponential Smoothing and ARIMA processesBenjamin EtienneBlockedUnblockFollowFollowingFeb 9TL;DR: In this article you’ll learn the basics steps to performing…

## Time Series Forecasting (1): Initial analysis

Is all the data in the desired format?Looking at the statistics: Are there outliers?Looking for stationarity and autocorrelationTrend and seasonality…

## Time Series Analysis Tutorial Using Financial Data

I used ARIMA and SARIMAX models from StatsModels and the popular Facebook Prophet model as well. The first thing I…

## Almost Everything You Need to Know About Time Series

Almost Everything You Need to Know About Time SeriesUnderstand moving average, exponential smoothing, stationarity, autocorrelation, SARIMA, and moreMarco PeixeiroBlockedUnblockFollowFollowingFeb 5Photo by Lukas…

## Predicting a Startup Valuation with Data Science

Is that round approximately average when compared to historical financing events, or is it an anomaly?At Radicle, a disruption research…

## A Comprehensive List of Handy R Packages

A Comprehensive List of Handy R PackagesStuff I have found super useful for work and lifeGang SuBlockedUnblockFollowFollowingJan 21Whether Python or R is…

Let’s use BSTS models and causal inference to find out…The R babynames package and causal inferenceThe code to accompany this…

## Predicting time series with deep learning, R and Apache MXNet

Predicting time series with deep learning, R and Apache MXNetAnkit KhediaBlockedUnblockFollowFollowingJan 18Multivariate time series forecasting is one of the most commonly…

## Time Series Data Munging — Lagging Variables that are Distributed Across Multiple Groups

If you lag 2 steps, the first two rows will be null etc. For this example, the index is already…

## Pierre de Wulf

Beware of Python dict. get()If you think that value = my_dict. get('my_key', 'default_value') is equivalent to value =…How we went…

## A Hands-On Introduction to Time Series Classification (with Python Code)

In the next section, we will look at the dataset for the problem which should help clear up any lingering…

## Fibonacci, Power Series and Big-O

While I like puzzles, I didn’t expect that I’d just be able to work this out, so I opened Google.…

## A Quick Start of Time Series Forecasting with a Practical Example using FB Prophet

A Quick Start of Time Series Forecasting with a Practical Example using FB ProphetYang LylaBlockedUnblockFollowFollowingJan 2Table of ContentsIntroductionTime Series AnalysisWhy Facebook Prophet?2.…

## Detecting Anomalies in Time Series Data: Deciphering the Noise and Zoning in on the Signals

Anomaly detection for time series data with deep learning – identifying the “unknown unknowns” One of the most effective ways…

## Introducing M3

The current implementation of the query engine is tied to M3DB but the design can support other time series databases.M3…

## A brief introduction to Slow Feature Analysis

This can be remedied by doing a non-linear expansion of the time series S first, then finding linear features of…

## Processing Time Series Data in Real-Time with InfluxDB and Structured Streaming

Processing Time Series Data in Real-Time with InfluxDB and Structured StreamingThis article focuses on how to utilize a popular open…

## Get a glimpse of future using time series forecasting using Auto-ARIMA and Artificial Intelligence

Get a glimpse of future using time series forecasting using Auto-ARIMA and Artificial IntelligenceVeer KhotBlockedUnblockFollowFollowingDec 14AI and futureCurrently, there is a…

## Visualizing The Madness of Crowds with Python

At the same time we’re going to create a new column for each of our assets which will capture the…

## Car De-registrations in Singapore: Can they be Predicted?

The data is in monthly series, with the first time point being Feb 1990..For illustration, the training and test data…

## A short tutorial on Fuzzy Time Series

But some key features distinguish the Fuzzy Time Series e turn it on a attractive option:ReadabilityManageabilitySimplicityScalabilityHereafter I going to assume…

## A short tutorial on Fuzzy Time Series — Part II

A short tutorial on Fuzzy Time Series — Part IIWith an case study on Solar EnergyIn the first part of this tutorial I briefly…